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Comment by healeycodes | Hacker News Reader

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healeycodes·

I welcome any improvements to my naive exploration in this article!

I've received two emails from readers:

- One suggested converting RGB to a color space that better matches human visual perception, like CIELAB.

- Another suggested compressing the color space by using K-means clustering (by guessing K as the number of threads)

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Is that a good idea? I don’t do embroidery but I’d guess people mix threads of different colour in the same area to merge them. As long as the image is original you can discard those areas as false positives instead of new colours; if you compress the image, that subtlety per thread is lost.

K means clustering the color space is certainly an interesting idea, though you might need n+1 colors as I’d guess the background color of the hoop is often prevalent.

Also: it seems like your query function is actually building the tree on each call? If so, that would slow it down a lot (though the lru cache is still a great idea!)

What are DMC threads? I tried to read the article, but without knowing that I don’t really get anything.

They are the colored threads that you stitch with. DMC is a brand but it’s also the colloquial term for the fixed set of colors that are commonly used and sold.

I’ll see if I can make that clearer — thanks.

So pantone but for dyed fiber instead of inks on paper...

Why not use Cannyedge detection for edge detection? It should work pretty well once you have a greyscale image, and then circle detection as you already do.

A color reference would help. Stitch something with standard thread samples and use that for comparison.

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